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Updated: May 22, 2025
Author Spotlight: Genetic Profiling for Fluorouracil Response in Gastric Cancer
Published on: May 10, 2024
Artificial intelligence-driven integration of single-cell RNA sequencing and transcriptome analysis to decipher
Ni Li1, Jinquan Lin2,3, Chunyu Wang3
1Health Management Center, People's Hospital of Guilin, Guilin, 541002, Guangxi, China.
Background:
Gastric cancer (GC) remains a global health challenge due to its high mortality rate and the lack of specific diagnostic methods. Tumor heterogeneity significantly hinders effective treatment, necessitating advanced techniques to dissect its complexity. Artificial intelligence (AI) offers transformative potential in uncovering intricate cellular dynamics and gene regulatory networks. This study leverages single-cell RNA sequencing (scRNA-seq) combined with transcriptome analysis, enhanced by AI-driven analytics, to explore the tumor microenvironment and identify novel prognostic markers and therapeutic targets in GC.
Methods:
scRNA-seq and transcriptome datasets of GC patients were analyzed using AI-enhanced methodologies to unravel tumor heterogeneity and microenvironmental dynamics. Macrophage subsets were identified as critical components within the GC microenvironment. High-variance gene screening in these subsets pinpointed apolipoprotein E (APOE) as a hub gene. Experimental validation of APOE expression in GC samples and functional studies in GC cell lines were conducted.
Results:
Bioinformatics and AI-enabled analyses confirmed the immunosuppressive role of APOE in GC. An immune-related survival model was developed to predict immunotherapy responses and patient prognoses. Mechanistically, APOE was found to induce immunosuppression through M2 macrophage polarization, promoting tumor progression and leading to poorer outcomes in GC patients.
Conclusion:
This study highlights the potential of AI-driven approaches in elucidating the role of APOE in GC progression. APOE's regulatory effects on M2 macrophages underscore its value as a prognostic marker and therapeutic target, paving the way for precision medicine in GC management.
Insights
Artificial intelligence identified apolipoprotein E (APOE) as a key driver of immunosuppression in gastric cancer (GC). APOE promotes tumor progression by polarizing M2 macrophages, highlighting its potential as a prognostic marker and therapeutic target for GC.
Area of Science:
- Oncology
- Immunology
- Bioinformatics
Background:
- Gastric cancer (GC) presents a significant global health burden with high mortality and limited diagnostic tools.
- Tumor heterogeneity complicates effective GC treatment, demanding advanced analytical approaches.
- Artificial intelligence (AI) shows promise in dissecting complex cellular dynamics and gene regulatory networks in cancer.
Purpose of the Study:
- To explore the tumor microenvironment in GC using AI-enhanced single-cell RNA sequencing (scRNA-seq).
- To identify novel prognostic markers and therapeutic targets within the GC tumor microenvironment.
- To elucidate the role of specific genes, particularly apolipoprotein E (APOE), in GC progression and immune evasion.
Main Methods:
- Analysis of scRNA-seq and transcriptome data from GC patients using AI-driven methodologies.
- Identification and characterization of macrophage subsets within the GC tumor microenvironment.
- High-variance gene screening to pinpoint hub genes, followed by experimental validation of APOE expression and function in GC cell lines.
Main Results:
- AI-enabled analyses confirmed the immunosuppressive function of APOE in gastric cancer.
- APOE was identified to induce immunosuppression via M2 macrophage polarization, promoting tumor progression.
- An immune-related survival model was developed, demonstrating APOE's association with poorer patient prognosis and predicting immunotherapy response.
Conclusions:
- AI-driven approaches effectively elucidate the role of APOE in GC pathogenesis.
- APOE's regulation of M2 macrophages establishes it as a valuable prognostic biomarker.
- Targeting APOE offers a potential therapeutic strategy for precision medicine in gastric cancer management.
